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Over the past years, synthetic biology has seen significant development, establishing a typical "Design-Build-Test-Learn (DBTL)" cycle for engineering cell factories. This cycle has been becoming an enabling methodology for smart breeding to accelerate the development of biomanufacturing. In the DBTL cycle, the testing step primarily aims to evaluate the phenotypes of constructed cell factories, which can provide a large amount of data for further learning and iterative optimization. Due to the complexity of cellular metabolic networks and regulatory mechanisms, as well as the complicated associations between genotypes and phenotypes, the design and construction of cell factories have traditionally involved long-term and labor-intensive iterative experiments. In synthetic biology, the construction of cell factories with designed synthetic pathways is often combined with random mutation and evolution to build up a large screening library, which always requires a high throughput and efficient technology and equipment in the testing step. The testing step is the rate-limiting process in the entire DBTL cycle, and its efficiency is largely dependent on chassis cells themselves, as well as the throughput of bioreactors and instruments needed for their phenotype testing. Here, this review article focuses on an overview of bioreactors and instruments with different throughput scales used for the phenotype testing in synthetic biology. We introduce their characteristics and application scenarios, including single-cell detecting and screening technology as well as pico-, nano-, micro-, milli-, and liter-scale bioreactors. Moreover, this article also points out the application potential of existing phenotype testing bioreactors and instruments, and illustrates how they can be selected for specific research purposes. Finally, the challenges and perspectives for phenotype testing bioreactors and instruments are summarized, which hopefully provides a reference for a wide range of synthetic biology researchers to properly select and use phenotype testing instruments.
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| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |
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